Unofficial Messari API client.
Project description
Messari
Unofficial Messari's Crypto Data API client in python
The library can be used for crypto prices, market data metrics, on-chain metrics, and qualitative information (asset profile). For more information, see Messari API Documentation
Installation:
use pip to install:
pip install messari
Authentication:
Most endpoints are accessible without an API key.
Pass API key in object initialization if required.
Example usage:
from messari import Messari
# initialize api client
# API Key is optional
messari = Messari(key='xxxxxxxxxxxxxxx')
# Get the paginated list of all assets and their metrics and profiles.
resp = messari.get_all_assets()
# Use query parameters
query = {
'with-profiles': True,
'with-metrics': True,
'fields': 'id,slug,symbol,metrics/market_data/price_usd'
}
resp = messari.get_all_assets(**query)
# set filter fields
fields='symbol,name,slug'
# Get basic metadata for an asset.
resp = messari.get_asset(asset_key='btc', fields=fields)
# Get all of our qualitative information for an asset.
fields='symbol,name,profile/general/overview/project_details'
resp = messari.get_asset_profile(asset_key='btc', fields=fields)
# Get all of our quantitative metrics for an asset.
fields = 'id,slug,symbol,market_data/price_usd,market_data/volume_last_24_hours'
resp = messari.get_asset_metrics(asset_key='btc', fields=fields)
# Get the latest market data for an asset.
fields = 'id,slug,symbol,market_data/price_usd,market_data/volume_last_24_hours'
resp = messari.get_asset_market_data(asset_key='btc', fields=fields)
# Lists all of the available timeseries metric IDs for assets.
resp = messari.list_asset_timeseries_metric_ids()
# Retrieve historical timeseries data for an asset.
query_params = {
'start': '2020-01-01',
'end': '2020-02-01',
'interval': '1d',
'columns': 'open,close',
'order': 'ascending',
'format': 'json',
'timestamp-format': 'rfc3339'
}
resp = messari.get_asset_timeseries(asset_key='bitcoin', metric_id='price', **query_params)
# Get the list of all exchanges and pairs that our WebSocket-based
# market real-time market data API supports.
fields = 'exchange_name,pair,last_trade_at'
resp = messari.get_all_markets(fields=fields)
# Retrieve historical timeseries data for a market.
query_params = {
'start': '2020-01-01',
'end': '2020-03-01',
'interval': '1d',
'columns': 'open,close',
'order': 'ascending',
'format': 'json',
'timestamp-format': 'rfc3339'
}
resp = messari.get_market_timeseries(market_key='binance-btc-usdt', metric_id='price', **query_params)
# Get the latest (paginated) news and analysis for all assets.
fields='title,content'
resp = messari.get_all_news(fields=fields)
# Get the latest (paginated) news and analysis for all assets.
fields='title,content'
resp = messari.get_news_for_asset(asset_key='btc', fields=fields)
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